Files
quantconnect--lean/Algorithm.CSharp/FillForwardEnumeratorOutOfOrderBarRegressionAlgorithm.cs
T
Adalyat Nazirov 1988ad1ae5 Bug 4925 daylight out of order bar (#4941)
* test

* wip

* Revert "Fix duplicated history entries when contains daylight saving time change (#4700)"

Use proper rounding down

* regression test

* remove unused parameters

* more tests

* fix name and comment

* improve regression test

* more tests: oanda market hours

* re-apply Exchange TZ to bar EndTime

* fix expected results

* we can't substract minute because it can harm algorithm on minute resolution; so we could use tick?

* rename prop: conflict with QCAlgorithm.StartDate

* do not log messages to pass travis ci log limit

* assign loghandler in AlgorithmSetupHandler

* reference to PR for more description

* due to https://github.com/QuantConnect/Lean/pull/5039 we don't need to override it manually
2020-12-28 16:24:33 -03:00

123 lines
5.1 KiB
C#

/*
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
using System;
using System.Collections.Generic;
using System.Linq;
using QuantConnect.Data;
using QuantConnect.Interfaces;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Regression test algorithm simply fetch and compare data of minute resolution around daylight saving period
/// reproduces issue reported in GB issue GH issue https://github.com/QuantConnect/Lean/issues/4925
/// related issues https://github.com/QuantConnect/Lean/issues/3707; https://github.com/QuantConnect/Lean/issues/4630
/// </summary>
public class FillForwardEnumeratorOutOfOrderBarRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private decimal _exptectedClose = 84.09m;
private DateTime _exptectedTime = new DateTime(2008, 3, 10, 9, 30, 0);
private Symbol _shy;
/// <summary>
/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
/// </summary>
public override void Initialize()
{
SetStartDate(2008, 3, 7);
SetEndDate(2008, 3, 10);
_shy = AddEquity("SHY", Resolution.Minute).Symbol;
// just to make debugging easier, less subscriptions
SetBenchmark(time => 1);
}
public override void OnData(Slice slice)
{
var trackingBar = slice.Bars.Values.FirstOrDefault(s => s.Time.Equals(_exptectedTime));
if (trackingBar != null)
{
if (!Portfolio.Invested)
{
SetHoldings(_shy, 1);
}
if (trackingBar.Close != _exptectedClose)
{
throw new Exception(
$"Bar at {_exptectedTime.ToStringInvariant()} closed at price {trackingBar.Close.ToStringInvariant()}; expected {_exptectedClose.ToStringInvariant()}");
}
}
}
/// <summary>
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
/// </summary>
public bool CanRunLocally { get; } = true;
/// <summary>
/// This is used by the regression test system to indicate which languages this algorithm is written in.
/// </summary>
public Language[] Languages { get; } = { Language.CSharp };
/// <summary>
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
/// </summary>
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Trades", "1"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "0%"},
{"Drawdown", "0%"},
{"Expectancy", "0"},
{"Net Profit", "0%"},
{"Sharpe Ratio", "0"},
{"Probabilistic Sharpe Ratio", "0%"},
{"Loss Rate", "0%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "0"},
{"Beta", "0"},
{"Annual Standard Deviation", "0"},
{"Annual Variance", "0"},
{"Information Ratio", "0"},
{"Tracking Error", "0"},
{"Treynor Ratio", "0"},
{"Total Fees", "$5.93"},
{"Fitness Score", "0.499"},
{"Kelly Criterion Estimate", "0"},
{"Kelly Criterion Probability Value", "0"},
{"Sortino Ratio", "79228162514264337593543950335"},
{"Return Over Maximum Drawdown", "-105.726"},
{"Portfolio Turnover", "0.998"},
{"Total Insights Generated", "0"},
{"Total Insights Closed", "0"},
{"Total Insights Analysis Completed", "0"},
{"Long Insight Count", "0"},
{"Short Insight Count", "0"},
{"Long/Short Ratio", "100%"},
{"Estimated Monthly Alpha Value", "$0"},
{"Total Accumulated Estimated Alpha Value", "$0"},
{"Mean Population Estimated Insight Value", "$0"},
{"Mean Population Direction", "0%"},
{"Mean Population Magnitude", "0%"},
{"Rolling Averaged Population Direction", "0%"},
{"Rolling Averaged Population Magnitude", "0%"},
{"OrderListHash", "-850144190"}
};
}
}